CONCEPT
Adaptive Learning
Learning to cope with events—Senge's term for the necessary but insufficient organizational learning that enables survival without transformation.
Adaptive learning, in Senge's framework, is learning that enables an organization to cope—to respond to market shifts, solve problems as they arise, adjust to competitive pressure, and maintain operations under changing conditions. It is necessary for organizational survival but insufficient for genuine transformation because it operates within existing mental models and structures, improving execution without expanding the organization's fundamental capacity to create. Distinguished from generative learning (which expands creative possibility), adaptive learning is reactive rather than proactive, problem-solving rather than problem-setting, optimizing within constraints rather than reimagining the constraints themselves. In the AI age, the distinction becomes existential: organizations that use AI for adaptive learning (doing existing work faster) remain executing organizations with better tools; organizations that use AI for generative learning (expanding into previously inaccessible capabilities) develop the judgment and systemic awareness that the transition demands.
In The You On AI Field Guide
Senge borrowed the distinction from Chris Argyris's single-loop and double-loop learning framework. Single-loop learning detects and corrects errors within existing operating assumptions—the thermostat that maintains temperature by turning heating on